Testing Corn (Zea mays L.) Preseason Regional Nitrogen Recommendation Models in South Dakota

Abstract

or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. R egional N recommendation models, such as yield goal based N recommendation models, have been used for corn production since the 1970s (Chang et al., 2003;Koch et al., 2004;Mulvaney et al., 2006). A generalized form of the regional yield goal model is ( )where NR is the recommended N rate (kg ha -1 ), k is a constant that ranges from 21.4 to 26.8 kg N Mg -1 corn grain, and N credits include soil NO 3 , N provided by legumes, and N in irrigation water. If the yield goal model is viewed as a simplified version of a mass balance equation, then the difference between the N recommendation and k(yield goal) represents the N provided by the various pools. The advantages of Eq. [1] are that the model is easy to use and many people agree with the concept behind the model (high crop yields require more N than low crop yields). Although not designed for site-specific applications, modifications of this model are used for this purpose (Chang et al., 2003).A disadvantage with using a yield goal N model is that there is a poor relationship between yield and the EONR because it does not consider (i) water as a nutrient, (ii) N mineralization, and (iii) synergistic relationships between water, N, and the microbial community (Kim et al., 2008). Kim et al. (2008) reported a synergistic relationship between N and water in a corn study. Therefore, these results have been attributed to inaccurate assessment of N mineralization. Also, the excessive application of water in some states causes major N losses through leaching and denitrification. As a result, many states have dropped or modified the yield goal based recommendation is favor of unique recommendation models for each state. For example, (i) the South Dakota and Nebraska models consider yield goals while the Minnesota and Iowa models do not; (ii) the South Dakota model considers 100% of the NO 3 -N contained in the surface 60 cm, while the Nebraska model considers 50% of the NO 3 -N contained in the surface 120 cm, and the western Minnesota model considers 60% of the NO 3 -N in the surface 60 cm; and (iii) only the Nebraska model considers organic matter. Three of the models (Nebraska, western Minnesota, and Iowa) consider the fertilizer cost/corn price ratio in the N recommendation, while the South Dakota model does not.Validations of regional yield goal based N models for sitespecific and whole-field applications have been mixed (Fox and Piekielek, 1995;Lory and Scharf, 2003). These results are attributed to: (i) scaling problems, i.e., using models designed for a specific purpose for applications that have not been validated (Mulvaney et al., 2006); (ii) using simplistic models that do not account for synergistic relationships between N and water (Kim et al., 2008); (iii) using NO 3 -N as an estimator of the soil N pool; and (iv) using N recommendation models that do not account for local climatic conditions. Five general a...

Delta yield–based optimal nitrogen rate estimates for corn are often economically sound

“…Kim et al. (2013) also observed increased accuracy (increased correlation) of EONR estimations by dY as PR increased; however, in our data correlations between estimated and actual EONR were strong across the PR range evaluated (Table 2). Price sensitivity for the frequency of observations within the various loss categories were evaluated within the minimum–maximum range of corn and N fertilizer prices observed during 2009–2018.…”

“…We speculate that there are several explanations for limited adoption of the dY concept to estimate corn fertilizer N requirements. For example, the dY‐EONR relationships described earlier cause a lack of confidence in EONR estimations using dY because sometimes only about half of the variability is reported to be explained (Kachanoski et al., 1996; Lory & Scharf, 2003) or sometimes is reported to be poorly correlated (Kim et al., 2013). Also, the inability of some dY‐EONR models identified above to generate a 0 kg N ha −1 EONR estimate when dY is equal to 0 Mg ha −1 or models that provide a relatively constant EONR estimate at higher dY have called into question the reliability of these models at either low or high dY.…”

Dynamic Model Improves Agronomic and Environmental Outcomes for Maize Nitrogen Management over Static Approach

“…Thompson et al (2015) found that a crop simulation model performed better than crop canopy reflectance sensing in providing in‐season sidedress N recommendations for experimental sites in Missouri, Nebraska, and North Dakota but still had an estimated (by digitizing the published data) RMSE of 70 kg N ha −1 , (compared with 34 kg N ha −1 for Adapt‐N in our study). Adapt‐N's ability to predict the EONR was also more precise and was an improvement over most RMSE values presented for five different Midwest static state regional N recommendations (Kim et al, 2013). These results demonstrate that accounting for in‐season weather effects and site‐specific growing conditions such as weather can improve the prediction of the EONR.…”

Strengths and Limitations of Nitrogen Rate Recommendations for Corn and Opportunities for Improvement

“…While fertilizer rate recommendations based on response trials and economic return is not a new concept (Johnson, 1953;Heady and Pesek, 1954), emphasis on maximum return and adjustment for varying N and corn prices disappeared as implementation of the yield-goal system relating N fertilization requirement to attainable yield became popular. Also, adjustment for N/corn grain price ratio can improve rate recommendations (Kim et al, 2013). …”